A practical approach to feature selection
ML92 Proceedings of the ninth international workshop on Machine learning
Estimating attributes: analysis and extensions of RELIEF
ECML-94 Proceedings of the European conference on machine learning on Machine Learning
Fuzzy logic and neurofuzzy applications explained
Fuzzy logic and neurofuzzy applications explained
Pattern Recognition Letters
Pattern Recognition Letters - Special issue on fuzzy set technology in pattern recognition
Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
About the use of fuzzy clustering techniques for fuzzy model identification
Fuzzy Sets and Systems
Data mining: practical machine learning tools and techniques with Java implementations
Data mining: practical machine learning tools and techniques with Java implementations
Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
Machine Learning
Fuzzy Algorithms: With Applications to Image Processing and Pattern Recognition
Fuzzy Algorithms: With Applications to Image Processing and Pattern Recognition
A fuzzy c-means variant for the generation of fuzzy term sets
Fuzzy Sets and Systems - Theme: Modeling and learning
Application of Fuzzy Logic to Approximate Reasoning Using Linguistic Synthesis
IEEE Transactions on Computers
Rule-based modeling: precision and transparency
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Linguistic models and linguistic modeling
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Modified Gath-Geva fuzzy clustering for identification of Takagi-Sugeno fuzzy models
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Linguistic models as a framework of user-centric system modeling
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
A new approach to fuzzy modeling
IEEE Transactions on Fuzzy Systems
Fuzzy modeling of high-dimensional systems: complexity reduction and interpretability improvement
IEEE Transactions on Fuzzy Systems
Designing fuzzy inference systems from data: An interpretability-oriented review
IEEE Transactions on Fuzzy Systems
Takagi-Sugeno fuzzy modeling incorporating input variables selection
IEEE Transactions on Fuzzy Systems
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The objective of this work is to present a fuzzy modeling method based on the conditional fuzzy clustering algorithm - the Fuzzy-CCM (Fuzzy Conditional Clustering Modeling) method. The balance between interpretability and accuracy of fuzzy rules is addressed by means of the definition of contexts formed with a small number of input variables and the generation of clusters conditioned by the context defined. The rules are generated in a different format which have linguistic variables with their values as well as groups. Some experiments have been run using different domains in order to validate the proposed approach and to compare the results with the ones obtained with the Wang&Mendell; and FCMeans methods. The advantages of the method, the experiments and the results obtained are discussed.